Night-to-night variability of sleep apnea detected by cyclic variation of heart rate during long-term continuous ECG monitoring

Study on OSA screening and influencing factors in community-based elderly hypertensive patients based on single-lead wearable ECG devices

PURPOSE

Assessing whether single-lead ECG can be effectively and relatively inexpensively used in large-scale OSA screening, and identifying factors influencing moderate-to-severe OSA among elderly hypertensive patients without atypical symptoms in primary care.

METHODS

The study gathered data from 15 medical institutions in Ningxia between January and December 2022 using cloud platforms. The dataset included basic information and 72-h ECG monitoring for 2573 hypertensive patients over 65. OSA screening was conducted using the single-lead wearable ECG devices based on the ACAT algorithm. A multivariable logistic regression identified the main factors affecting OSA severity in these patients, and the AUC was used to assess the model's predictive accuracy.

RESULTS

The study found an OSA detection rate of 87.10%, with 55.42% being moderate to severe cases. Key risk factors associated with developing moderate-to-severe OSA included cardiac irregularities like supraventricular extrasystole and atrioventricular block, male gender, lifestyle factors like alcohol consumption and smoking, and health indicators such as SDNN ≤ 100 ms, abnormal LF/HF ratio, BMI, and age. The model's accuracy for predicting OSA, indicated by a ROAUC of 0.625, was moderate. Factors like gender, tea consumption, stroke history, and ventricular tachycardia were also independently linked to OSA severity.

CONCLUSION

This study combines single-lead wearable ECG devices with the ACAT algorithm for OSA screening in Ningxia, China. Initial screening identified 87.10% of participants as having OSA, with 55.42% being moderate to severe cases. This suggests a convenient, low-cost, and repeatable ECG-based method for OSA screening, potentially improving early detection and management of OSA by identifying potential risk factors.

Individual heart failure patient variability in nocturnal hypoxia and arrhythmias

Traditional heart failure research often uses daytime population parameter estimates to assess hypoxia and arrhythmias. This approach might not accurately represent heart failure patients as nighttime cardiac behaviors offer crucial insights into their health, especially regarding oxygen levels and heart rhythms. We conducted a prospective study on nocturnal oxygen saturation and heart rate in home-dwelling heart failure patients over 6 nights. Patients were recruited from the Walter Reed National Military Medical Center heart failure clinic. Criteria included a clinical diagnosis of heart failure, a New York Heart Association (NYHA) classification of I to III, ages between 21 to 90, cognitive intactness, capability to use the wearable device, and willingness to use the device for 6 consecutive nights. Average oxygen saturation was 92% with individual readings ranging from 40% to 100%. The mean heart rate was 72 beats per minute (bpm), but individual rates ranged from 18 bpm to a high of 296 bpm. A significant drop in oxygen levels and sleep arrhythmias were consistently observed among participants. Heart failure patients demonstrate notable and variable desaturations and arrhythmias across multiple nights. A single-night sleep study or a 24-hour heart rate monitor may not comprehensively depict patients' oxygenation and heart rate irregularities. Our research highlights wearable devices' potency in medical research for capturing essential nocturnal data. In only 6 nights, we gleaned invaluable clinical insights for optimizing patient care. This study is pioneering, being the first to intensively examine nighttime oxygen levels and heart rates in home-based heart failure patients.

Piezoelectric rubber sheet sensor: a promising tool for home sleep apnea testing

PURPOSE

This study aimed to develop an unobtrusive method for home sleep apnea testing (HSAT) utilizing micromotion signals obtained by a piezoelectric rubber sheet sensor.

METHODS

Algorithms were designated to extract respiratory and ballistocardiogram components from micromotion signals and to detect respiratory events as the characteristic separation of the fast envelope of the respiration component from the slow envelope. In 78 adults with diagnosed or suspected sleep apnea, micromotion signal was recorded with a piezoelectric rubber sheet sensor placed beneath the bedsheet during polysomnography. In a half of the subjects, the algorithms were optimized to calculate respiratory event index (REI), estimating apnea-hypopnea index (AHI). In the other half of subjects, the performance of REI in classifying sleep apnea severity was evaluated. Additionally, the predictive value of the frequency of cyclic variation in heart rate (Fcv) obtained from the ballistocardiogram was assessed.

RESULTS

In the training group, the optimized REI showed a strong correlation with the AHI (r = 0.93). Using the optimal cutoff of REI ≥ 14/h, subjects with an AHI ≥ 15 were identified with 77.8% sensitivity and 90.5% specificity. When applying this REI to the test group, it correlated closely with the AHI (r = 0.92) and identified subjects with an AHI ≥ 15 with 87.5% sensitivity and 91.3% specificity. While Fcv showed a modest correlation with AHI (r = 0.46 and 0.66 in the training and test groups), it lacked independent predictive power for AHI.

CONCLUSION

The analysis of respiratory component of micromotion using piezoelectric rubber sheet sensors presents a promising approach for HSAT, providing a practical and effective means of estimating sleep apnea severity.

Effects of Sacubitril-Valsartan on Clinical, Echocardiographic, and Polygraphic Parameters in Patients Affected by Heart Failure With Reduced Ejection Fraction and Sleep Apnea

Background

Heart failure with reduced ejection fraction (HFrEF) is a clinical condition frequently diagnosed in clinical practice. In patients affected by HFrEF, sleep apnea (SA) can be detected among the most frequent comorbidities. Sacubitril–valsartan (sac/val) association has been proven to be effective in reducing disease progression and all-cause mortality in HFrEF patients. Sac/val treatment can potentially attenuate SA development via several pathophysiologic mechanisms, including improvement of global hemodynamics, reduction of extracellular fluid overload, and decrease of sympathetic neural activity.

Methods

We recruited 132 patients affected by HFrEF and SA, already under treatment with continuous positive airway pressure (CPAP), which was discontinued 24 h before the scheduled study timepoints. Physical examination, echocardiography, nocturnal cardio-respiratory monitoring, and laboratory tests were performed in each patient at baseline and after a 6-month treatment with sac/val.

Results

After 6 months, sac/val induced statistically significant changes in clinical, hemodynamic, biohumoral (NT-proBNP, serum electrolytes, creatinine, and uric acid), and echocardiographic parameters. In particular, cardiac index (CI), both atrial and ventricular volumes and global longitudinal strain (GLS) improved. Moreover, polysomnography, carried out during a temporary CPAP interruption, revealed a significant reduction in global apnea-hypopnea index (AHI) value (p < 0.0001), central AHI (p < 0.0001), obstructive AHI (p < 0.0001), oxygen desaturation index (ODI) (p < 0.0001), and percentage time of saturation below 90% (TC90) (p < 0.0001). The changes of CI, estimated glomerular filtration rate (eGFR), NT-proBNP, and tricuspid annular plane excursion (TAPSE) contributed to 23.6, 7.6, 7.3, and 4.8% of AHI variability, respectively, and the whole model accounted for a 43.3% of AHI variation.

Conclusions

Our results suggest that treatment with sac/val is able to significantly improve the cardiorespiratory performance of patients with HFrEF and SA, integrating the positive impact of CPAP. Thus, both CPAP and sac/val therapy may synergistically contribute to lower the risks of both cardiac and pulmonary complications in HFrEF patients with SA.

Assessment of autonomic function by long-term heart rate variability: beyond the classical framework of LF and HF measurements

In the assessment of autonomic function by heart rate variability (HRV), the framework that the power of high-frequency component or its surrogate indices reflects parasympathetic activity, while the power of low-frequency component or LF/HF reflects sympathetic activity has been used as the theoretical basis for the interpretation of HRV. Although this classical framework has contributed greatly to the widespread use of HRV for the assessment of autonomic function, it was obtained from studies of short-term HRV (typically 5‑10 min) under tightly controlled conditions. If it is applied to long-term HRV (typically 24 h) under free-running conditions in daily life, erroneous conclusions could be drawn. Also, long-term HRV could contain untapped useful information that is not revealed in the classical framework. In this review, we discuss the limitations of the classical framework and present studies that extracted autonomic function indicators and other useful biomedical information from long-term HRV using novel approaches beyond the classical framework. Those methods include non-Gaussianity index, HRV sleep index, heart rate turbulence, and the frequency and amplitude of cyclic variation of heart rate.